mlsanityData to 14 Oct 2026

CRLLK: Constrained Reinforcement Learning for Lane Keeping in Autonomous Driving

arXiv 2503.22248 ↗First posted 28 Mar 2025cs.LG cs.ROcited by 1

On the map: End-to-end autonomous driving → Reinforcement learning for driving

also in 1 more
Abstract (arXiv)

Lane keeping in autonomous driving systems requires scenario-specific weight tuning for different objectives. We formulate lane-keeping as a constrained reinforcement learning problem, where weight coefficients are automatically learned along with the policy, eliminating the need for scenario-specific tuning. Empirically, our approach outperforms traditional RL in efficiency and reliability. Additionally, real-world demonstrations validate its practical value for real-world autonomous driving.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Reinforcement learning for driving, one of 9 directions in End-to-end autonomous driving. Builds on 6 of its 22 references that are in the map. First posted on arXiv 28 Mar 2025.

Builds on

6 of 22 references.

References · 6

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,258
  3. 2018Reward Constrained Policy Optimizationcited by 417
  4. 2016End-to-End Deep Reinforcement Learning for Lane Keeping Assistcited by 27
  5. 2020Robust Reinforcement Learning-based Autonomous Driving Agent for Simulation and Real Worldcited by 12
  6. 2020RACE: Reinforced Cooperative Autonomous Vehicle Collision AvoidancEcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Neuro-symbolic Action Masking for Deep Reinforcement Learningcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025BLIP-FusePPO: A Vision-Language Deep Reinforcement Learning Framework for Lane Keeping in Autonomous Vehicles
  2. 2020Meta Reinforcement Learning-Based Lane Change Strategy for Autonomous Vehicles
  3. 2024Optimizing Low-Speed Autonomous Driving: A Reinforcement Learning Approach to Route Stability and Maximum Speed
  4. 2023Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors
  5. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
  6. 2022Safe Decision-making for Lane-change of Autonomous Vehicles via Human Demonstration-aided Reinforcement Learning
  7. 2025Tackling Snow-Induced Challenges: Safe Autonomous Lane-Keeping with Robust Reinforcement Learning
  8. 2024Autonomous Algorithm for Training Autonomous Vehicles with Minimal Human Intervention